A review on Data Compression Techniques in Cloud Computing
Supreet Kaur, Amanpreet Kaur , , ,
Affiliations
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Abstract
Cloud Computing has become a crucial aspect in today's era of technology in the world and it has grown past all the boundaries.
There is a need to connect resources and users without having physical connection. The high demand for data processing and leads to high
computational requirement which is usually not available at the user's end. This has encouraged several companies to provide services over the
cloud in the form of service, storage, platform etc. But along with its advantages cloud computing has brought with it several challenges like security, storage, scheduling etc. Storage in Cloud computing forms a very important part as the need of virtual space to store our large data has
grown over these years. But the speed of uploading and downloading limits the processing time and there is a need to solve this issue of large
data handling. This thesis aims at solving this problem using compression technique on multimedia data. A novel Genetic compression technique
will be developed and applied on multimedia data and used in cloud computing for managing such large data. The implementation will be done in
CloudSim toolkit and the results will be compared against the existing schemes.
Citation
Supreet Kaur,Amanpreet Kaur."A review on Data Compression Techniques in Cloud Computing ". International Journal of Computer Engineering In Research Trends (IJCERT) ,ISSN:2349-7084 ,Vol.2, Issue 05,pp.319-321, May - 2015, URL :https://ijcert.org/ems/ijcert_papers/V2I59.pdf,
Keywords : Cloud Computing, Storage Space Bandwidth.
References
[1] Srinivas, J., K. Venkata Subba Reddy, and A. MOIZ Qyser. "Cloud
Computing Basics." International Journal of Advanced Research in
Computer and Communication Engineering, 1 (5) (2012).
[2] Nicolae, Bogdan. "High throughput data-compression for cloud
storage." Data Management in Grid and Peer-to-Peer Systems. Springer
Berlin Heidelberg, 2010. 1-12.
[3] C. Yang et al., A spatiotemporal compression based approach for
efficient big data processing on cloud, J. Comput. System Sci. (2014)
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